Time-Dependent Seismic Hazard Analysis for Induced Seismicity: The Case of St Gallen (Switzerland), Geothermal Field

Abstract

Reliable seismic hazard analyses are crucial to mitigate seismic risk. When dealing with induced seismicity the standard Probabilistic Seismic Hazard Analysis (PSHA) has to be modified because of the peculiar characteristics of the induced events. In particular, the relative shallow depths, small magnitude, a correlation with field operations, and eventually non-Poisson recurrence time. In addition to the well-known problem of estimating the maximum expected magnitude, it is important to take into account how the industrial field operations affect the temporal and spatial distribution of the earthquakes. In fact, during specific stages of the project the seismicity may be hard to be modelled as a Poisson process—as usually done in the standard PSHA—and can cluster near the well or migrate toward hazardous known or—even worse—not known faults. Here we present a technique in which we modify the standard PSHA to compute time-dependent seismic hazard. The technique allows using non-Poisson models (BPT, Weibull, gamma and ETAS) whose parameters are fitted using the seismicity record during distinct stages of the field operations. As a test case, the procedure has been implemented by using data recorded at St. Gallen deep geothermal field, Switzerland, during fluid injection. The results suggest that seismic hazard analyses, using appropriate recurrence model, ground motion predictive equations, and maximum magnitude allow the expected ground-motion to be reliably predicted in the study area. The predictions can support site managers to decide how to proceed with the project avoiding adverse consequences.

Improvements to seismicity forecasting based on a Bayesian spatio-temporal ETAS model

“…For a given forecasting interval, this leads to spatial distribution of the forecasted events and probability distribution of the number of events. The outcomes of this robust seismicity forecasting are directly applicable in adaptive daily aftershock hazard (e.g., 24 , 33 , 55 , 56 ) and risk assessment procedures (see e.g., 35 , 37 , 39 ).…”

Improvements to seismicity forecasting based on a Bayesian spatiotemporal ETAS model: Application to 2017-2019 Kermanshah seismic sequence in Western Iran

“…For a given forecasting interval, this leads to spatial distribution of the forecasted events and probability distribution of the number of events. The outcomes of this robust seismicity forecasting are directly applicable in adaptive daily aftershock hazard (e.g., 23,32,53,54 ) and risk assessment procedures (see e.g., 34,36,38 ). This work strives to improve different aspects of the fully probabilistic seismicity forecasting framework proposed in 27 .…”

Induced Earthquake Hazard by Geothermal Power Plants: Statistical Evaluation and Probabilistic Modeling

“…Their study emphasized the need for reevaluation of the risk by using updated data throughout a power plant's activity. Convertito et al (2021) also performed a time-dependent seismic hazard analysis of the St Gallen geothermal field. More recently, Khansefid et al (2022b) worked on recorded ground motions due to GPP activities to develop a set of ground motion models.…”